基于细胞自动机模型电力网络攻击预测技术  

Cellular automata model based power network attack prediction technology

作　　者：冶莉娟 王亦婷 朱励程 Lijuan YE;Yiting WANG;Licheng ZHU(Qinghai Electric Power Company,Xining 810008,China;Qizhi Technology Co.,Ltd.,Shanghai 200122,China)

机构地区：[1]国网青海省电力公司,青海西宁810008 [2]上海柒志科技有限公司,上海200122

出　　处：《电信科学》2023年第4期173-179,共7页Telecommunications Science

摘　　要：传统电力网络攻击范围预测技术的预测范围不够广,导致电力网络安全性提升效果不明显。为此,提出基于细胞自动机模型的电力网络攻击预测技术。搭建电力细胞自动机模型,将细胞自动机中的细胞看作电力细胞,建立细胞活力值转换规则,将其与攻击者执行攻击概率相结合,预测电力细胞的发展变化。根据中心电力细胞及邻域电力细胞的变化趋势预测电力网络攻击。实验结果表明:在时间因素影响下,提出的基于细胞自动机模型电力网络攻击预测技术的预测攻击节点位置与原始节点基本一致,预测后负荷切除量始终在100 MW以下,本文所提技术的有效性更好。The prediction range of the traditional power network attack range prediction technology was not wide enough,resulting in the poor effect of power network security improvement.For this reason,a power network attack prediction technology based on cellular automata model was proposed.A cellular automata model was built,regarding the cells in the cellular automata as power cells,a cell vitality value conversion rule was established and combined with the attack probability of attackers to predict the development and change of power cells.The power network attack was predicted according to the change trend of central power cells and neighboring power cells.The experimental result shows that,under the influence of time factors,the predicted attack node location of the proposed power network attack prediction technology based on cellular automata model is basically consistent with the original node,and the predicted load removal is always below 100 MW,the proposed technology is more effective.

关 键 词：细胞自动机 电力网络 攻击概率 网络信息 预测模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]